A Hybrid Optimization Technique for Fixed and Variable Head Short-Term Hydrothermal Scheduling

Abstract

The optimal short-term scheduling of hydrothermal plants plays an important role in the planning the operation of the power system. In short-term hydrothermal scheduling, the hydro-electric and thermal power generation is optimized to minimize the total operating cost of the thermal plant. The problem of short-term hydrothermal scheduling (STHTS) is complex due to consideration of power balance equality constraint, hydraulic constraint of water discharge rate equality constraint and non-linear cost characteristics of thermal units due to valve point loading effect. In this dissertation, a hybrid optimization technique is used to solve the problem of fixed and variable head STHTS. The hybrid optimization technique combines dynamic multi-swarm particle swarm optimizer (DMSPSO) and sequential quadratic programming (SQP). DMSPSO is a global search technique used for exploration of the search space and the SQP is a local search technique used for fine tuning of results obtained from DMSPSO. The proposed algorithm has been tested on various fixed and variable head hydrothermal test system. The results obtained will proves the effectiveness of the proposed technique.